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Article

High-Resolution Gridded Population Datasets: Exploring the Capabilities of the World Settlement Footprint 2019 Imperviousness Layer for the African Continent

1
German Aerospace Center (DLR), German Remote Sensing Data Center (DFD), Oberpfaffenhofen, D-82234 Wessling, Germany
2
Center for Information Earth Science Information Network (CIESIN), The Earth Institute, Columbia University, Palisades, NY 10964, USA
3
WorldPop, School of Geography and Environmental Science, University of Southampton, Southampton SO17 1BJ, UK
*
Author to whom correspondence should be addressed.
Academic Editor: Victor Mesev
Remote Sens. 2021, 13(6), 1142; https://doi.org/10.3390/rs13061142
Received: 17 February 2021 / Revised: 11 March 2021 / Accepted: 15 March 2021 / Published: 17 March 2021
The field of human population mapping is constantly evolving, leveraging the increasing availability of high-resolution satellite imagery and the advancements in the field of machine learning. In recent years, the emergence of global built-area datasets that accurately describe the extent, location, and characteristics of human settlements has facilitated the production of new population grids, with improved quality, accuracy, and spatial resolution. In this research, we explore the capabilities of the novel World Settlement Footprint 2019 Imperviousness layer (WSF2019-Imp), as a single proxy in the production of a new high-resolution population distribution dataset for all of Africa—the WSF2019-Population dataset (WSF2019-Pop). Results of a comprehensive qualitative and quantitative assessment indicate that the WSF2019-Imp layer has the potential to overcome the complexities and limitations of top-down binary and multi-layer approaches of large-scale population mapping, by delivering a weighting framework which is spatially consistent and free of applicability restrictions. The increased thematic detail and spatial resolution (~10 m at the Equator) of the WSF2019-Imp layer improve the spatial distribution of populations at local scales, where fully built-up settlement pixels are clearly differentiated from settlement pixels that share a proportion of their area with green spaces, such as parks or gardens. Overall, eighty percent of the African countries reported estimation accuracies with percentage mean absolute errors between ~15% and ~32%, and 50% of the validation units in more than half of the countries reported relative errors below 20%. Here, the remaining lack of information on the vertical dimension and the functional characterisation of the built-up environment are still remaining limitations affecting the quality and accuracy of the final population datasets. View Full-Text
Keywords: gridded population distribution mapping; large-scale population distribution modelling; World Settlement Footprint; percent of impervious surface; accuracy assessment; dasymetric modelling; sustainable development gridded population distribution mapping; large-scale population distribution modelling; World Settlement Footprint; percent of impervious surface; accuracy assessment; dasymetric modelling; sustainable development
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MDPI and ACS Style

Palacios-Lopez, D.; Bachofer, F.; Esch, T.; Marconcini, M.; MacManus, K.; Sorichetta, A.; Zeidler, J.; Dech, S.; Tatem, A.J.; Reinartz, P. High-Resolution Gridded Population Datasets: Exploring the Capabilities of the World Settlement Footprint 2019 Imperviousness Layer for the African Continent. Remote Sens. 2021, 13, 1142. https://doi.org/10.3390/rs13061142

AMA Style

Palacios-Lopez D, Bachofer F, Esch T, Marconcini M, MacManus K, Sorichetta A, Zeidler J, Dech S, Tatem AJ, Reinartz P. High-Resolution Gridded Population Datasets: Exploring the Capabilities of the World Settlement Footprint 2019 Imperviousness Layer for the African Continent. Remote Sensing. 2021; 13(6):1142. https://doi.org/10.3390/rs13061142

Chicago/Turabian Style

Palacios-Lopez, Daniela, Felix Bachofer, Thomas Esch, Mattia Marconcini, Kytt MacManus, Alessandro Sorichetta, Julian Zeidler, Stefan Dech, Andrew J. Tatem, and Peter Reinartz. 2021. "High-Resolution Gridded Population Datasets: Exploring the Capabilities of the World Settlement Footprint 2019 Imperviousness Layer for the African Continent" Remote Sensing 13, no. 6: 1142. https://doi.org/10.3390/rs13061142

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